Persistent data structure

  • Types of data structure

    Data persistence is the longevity of data after the application that created it has been closed.
    In order for this to happen, the data must be written to non-volatile storage — a type of memory that can retain that information long-term, even if the application is no longer running..

  • Types of data structure

    Persistent data is any data stored on a persistent storage medium.
    A persistent (or non-volatile) storage medium is a medium where the data remains intact after it has been written, until it is overwritten.
    This includes flash memory (SSDs, USB sticks), hard disks, magnetic tape, and optical media..

  • What are persistent data models?

    A persistence model assumes that the future value of a time series is calculated under the assumption that nothing changes between the current time and the forecast time..

  • What is persistent data structure with example?

    A data structure is said to be persistent if it is capable to maintaining its previous updates as separate versions and each version can be accessed and updated accordingly.
    It makes the data structure immutable and thread safe.
    For example, String class object in Java is immutable..

  • What is the meaning for persistent data?

    Persistent data is any data stored on a persistent storage medium.
    A persistent (or non-volatile) storage medium is a medium where the data remains intact after it has been written, until it is overwritten.
    This includes flash memory (SSDs, USB sticks), hard disks, magnetic tape, and optical media..

  • Why use persistent data structures?

    Ordinary data structures are ephemeral in the sense that a change to the structure destroys the old version, leaving only the new version available for use.
    In contrast, a persistent structure allows access to any version, old or new, at any time..

  • Persistent stack is a very nice data structure since all operations have the exact same asymptotic complexity as in the mutable implementation, but provide great benefits that mutable implementation doesn't.
    When we will explore other persistent data structures we will learn that this isn't always the case.
A persistent data structure is a data structure that always preserves the previous version of itself when it is modified. They can be considered as 'immutable' as updates are not in-place. A data structure is partially persistent if all versions can be accessed but only the newest version can be modified.
Ordinary data structures are ephemeral in the sense that a change to the structure destroys the old version, leaving only the new version available for use. In contrast, a persistent structure allows access to any version, old or new, at any time.

Partial versus full persistence

In the partial persistence model, a programmer may query any previous version of a data structure, but may only update the latest version

Techniques for preserving previous versions

One method for creating a persistent data structure is to use a platform provided ephemeral data structure such as an array to store the data

Generalized form of persistence

Path copying is one of the simple methods to achieve persistency in a certain data structure such as binary search trees

Applications of persistent data structures

One of the useful applications that can be solved efficiently using persistence is the Next Element Search

Examples of persistent data structures

Perhaps the simplest persistent data structure is the singly linked list or cons-based list


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